Agent skill
agentic-layer-audit
Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/agentic-layer-audit
SKILL.md
Agentic Layer Audit Skill
Evaluate a codebase's agentic layer maturity and identify investment opportunities.
When to Use
- Assessing current agentic layer coverage
- Identifying gaps in automation
- Planning agentic layer investments
- Measuring progress toward 50%+ agentic time
Core Concept
"Am I working on the agentic layer or am I working on the application layer?"
This skill helps answer that question by auditing what exists.
Audit Checklist
1. Commands Directory
Check for .claude/commands/ or equivalent:
Look for:
- chore.md # Chore planning template
- bug.md # Bug fix template
- feature.md # Feature planning template
- implement.md # Implementation HOP
- test.md # Test execution template
- review.md # Review template
2. Specs Directory
Check for specs/ or equivalent:
Look for:
- Issue-based specs (issue-*.md)
- Generated plans (chore-*.md, feature-*.md)
- Deep specs (complex multi-file architectures)
3. ADW Directory
Check for adws/ or equivalent:
Look for:
- adw_modules/agent.py # Core agent execution
- Gateway scripts (adw_prompt.py, adw_slash_command.py)
- Composed workflows (adw_*_*.py)
- Triggers (trigger_*.py)
4. Hooks Directory
Check for .claude/hooks/ or equivalent:
Look for:
- pre_tool_use hooks
- post_tool_use hooks
- user_prompt_submit hooks
5. Agent Output Directory
Check for agents/ or equivalent:
Look for:
- ADW ID directories
- State files (adw_state.json)
- Output files (cc_*.jsonl, cc_*.json)
6. Worktree Support
Check for trees/ or equivalent:
Look for:
- Git worktree setup
- Isolation configuration
- Port allocation patterns
Coverage Scoring
| Component | Points | Present? |
|---|---|---|
| .claude/commands/ | 20 | |
| specs/ | 15 | |
| adws/ | 25 | |
| adw_modules/agent.py | 20 | |
| hooks/ | 10 | |
| agents/ | 5 | |
| trees/ | 5 |
Total: 100 points
| Score | Level | Recommendation |
|---|---|---|
| 0-20 | None | Start with minimum viable layer |
| 21-40 | Basic | Add composed workflows |
| 41-60 | Developing | Add hooks and triggers |
| 61-80 | Advanced | Add worktree isolation |
| 81-100 | Complete | Focus on optimization |
Key Memory References
- @agentic-layer-structure.md - What to look for
- @the-guiding-question.md - Why this matters
- @agentic-vs-application.md - Layer separation
Output Format
## Agentic Layer Audit Report
**Project:** {name}
**Audit Date:** {date}
**Coverage Score:** {score}/100
### Components Found
- [x] .claude/commands/ (5 templates)
- [x] specs/ (12 specs)
- [ ] adws/ (not found)
- [ ] hooks/ (not found)
### Maturity Level
{Level} - {Recommendation}
### Gaps Identified
1. No ADW scripts for workflow orchestration
2. No hooks for event-driven automation
3. No worktree isolation for parallelization
### Recommended Investments
1. Create adws/adw_modules/agent.py
2. Add gateway script (adw_prompt.py)
3. Create composed workflow for common tasks
### Time Investment Analysis
- Current: ~20% agentic layer
- Target: 50%+ agentic layer
- Gap: Need 30% more investment in agentic work
Anti-Patterns to Identify
- Commands exist but no specs (templates unused)
- Specs exist but no ADWs (manual execution)
- Many one-off scripts instead of composed workflows
- Application layer dominant (>70% of codebase)
Version History
- v1.0.0 (2025-12-26): Initial release
Last Updated
Date: 2025-12-26 Model: claude-opus-4-5-20251101
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